The COVID-19 Coronavirus is taking the world by storm, and our most at-risk demographic is in a vulnerable position. As of April 2020, nearly 10,000 U.S. coronavirus deaths were connected to nursing home residents or caregivers – and it’s only continuing to rise. We know social distancing is working, but with nursing homes on lockdown, there is an urgent call for new early-detection protocols. Do data and smart gadgets have the answers to mitigating Coronavirus risks and saving lives?
Nursing Homes: Unfortunate Front Lines
Between March 23 and March 30, 2020, the rate of COVID-19 cases across long-term care patients spiked a massive 172%. Furthermore, at least 2,300 American nursing facilities have reported cases of COVID-19.
As of April 13, nearly 400 post-acute homes have been affected by an outbreak in New Jersey alone. This has resulted in more than 1,500 deaths for the state’s most at-risk population.
The Life Care Center of Kirkland (Seattle, Washington) was one of the first U.S. epicenters of the outbreak. More than ⅔ of residents have tested positive for COVID-19, and nearly 40 residents have died from the virus while in the facility.
Many American health experts have indicated a lack of testing and data gathering as the root cause. According to these health experts, the aforementioned tools are crucial in developing new strategies to combat the virus.
What Data Can Show Us
Worldwide organizations have begun making efforts to use emerging technologies and data science to combat the virus. For example, the World Health Organization (WHO) teamed up with Facebook, Microsoft, Twitter, and other large tech companies to host a coronavirus “hackathon.” Similarly, The Rockefeller Foundation committed $20 million to the development of better data-science tools for tracking and managing the spread of COVID-19.
The issue isn’t the lack of data surrounding COVID-19, it’s determining what is the most relevant data to the cause.
The most crucial pinpoints we need knowledge of regarding COVID-19 are:
- The severity of the virus
- Risks factors
- How COVID-19 spreads
- Societal and environmental context
To gain knowledge of this information, local data must be produced.
Why Specialized Data Matters
If we rely solely on macro data to build predictive models of COVID-19’s future, we may miss vital differences in the way this epidemic is spreading. Data saves lives, and by having access to local data, we won’t miss a beat.
The data we must take into account are:
- Geographic locations of COVID-19
- Cultural customs and behaviors of the infected
- Socioeconomic factors of the infected
For example: In 2010, a cholera epidemic in Haiti killed 7,000 and infected half a million others. It took weeks for official sources to report details; however, on Twitter, news of the disease traveled far more quickly.
Contraction Questions: Wound Care
Local data is not only important for knowing the state of COVID-19, but it’s also important to understand unknown ways it can spread. A common question in the news is whether or not COVID-19 can be spread through open wounds and cuts.
Wound Care is complex, yet very essential. 8.1 million Americans require some form of long-term care, and a huge percentage suffer wounds while in care. For example, up to 36% of home health patients (1.6 million people) suffer from major wounds, as well as up to 35% of hospice patients (500,000 people).
Furthermore, up to 35% of skilled nursing patients (300,000 people), and up to 27% of long-term acute care patients (219,000 people) suffer from the same. In total, up to 2.5 million seniors in care may require chronic wound care during the pandemic.
Elderly patients (aged 65+) also need postoperative wound monitoring due to higher risk for non-healing wounds and infections that require re-hospitalization. Elderly patients also account for 33% of ambulatory surgeries. All-in-all, 9.4 million people would require post-op surgical wound care during the pandemic.
More than 400 long-term care facilities across America have reported cases of COVID-19, which was nearly double the number of reported cases just one week earlier than this finding (March 30, 2020).
How Smart Technology Can Draw The Data You Need
There are many preventative measures against contracting the virus. For example, wearing a face mask and conducting routine temperature checks. However, technology can take you a step further in identifying specific indicators of early contraction.
UC San Francisco is studying 2,000 healthcare workers using Oura Ring. Their immediate goal is to detect onset symptoms of COVID-19, but their ultimate goal is to determine an algorithm to predict many illnesses before the patient falls physically ill.
The Oura Ring works by tracking symptoms through the finger, including respiration rate and body temperature. Overall, the ring can detect the patient’s temperature, heart rate, respiration rate, and more.
On the other hand, healthcare professionals can track the spread of the virus by using Kinsa, a smart thermometer.
Kinsa works by using anonymized data to track fevers across the country of its use. It pulls data from 500,000 thermometers in the nation of its location and compares its findings with 162,000 readings per day from its database of local thermometers.
Kinsa’s adapted algorithms detect fevers that are inconsistent with typical flu spread patterns. By doing so, the smart thermometer can identify likely clusters of the Coronavirus. With its massive data pool, Kinsa has consistently predicted the spread of COVID-19, accurately forecasting 2-3 weeks ahead of the CDC.
Technology For Specialized Populations
As previously mentioned, there is a drought of local data. Secure-IBD and Darwin AI have solutions.
Secure-IBD is a database of anonymized patient data for those with COVID-19 and irritable bowel disease. Caregivers around the world can contribute to the data collection. Caregivers across the globe can contribute to the data collection process, and each week, participants receive an updated summary of their data.
Darwin AI has released open source tools to assist researchers and clinicians diagnose and study COVID-19 through chest x-rays. COVID-Net is their neural network design to aid the diagnosis process, and COVIDx is their dataset of 5,941 chest x-rays across 2,839 patients.
A New Breakthrough in Early COVID-19 Outbreak Detection
Overall, temperature checks are too late. By switching early-detection protocols to internal checks, caregivers can detect the virus far earlier.
This can be done by the use of a Pulse Oximeter. By measuring residents’ oxygen levels twice daily, caregivers can use the oximeter’s data to find out their underlying problems before patients fully present COVID-19 symptoms in a nursing home setting. This can inform patients of their potential contraction up to 2 weeks earlier than a temperature check could.
How You Can Help From Home
You don’t have to be a data scientist to help contribute to the pool of local data.
Folding@home lets you share your unused computer power to aid research into potential cures for coronavirus and other diseases.
In the meantime, continue to take preventative measures such as staying socially distant and wearing your face mask. These two methods are among the most effective ways to prevent contracting and spreading COVID-19.